Special Issue "Dynamics and Control of Automated Vehicles"

A special issue of Vehicles (ISSN 2624-8921).

Deadline for manuscript submissions: 5 June 2021.

Special Issue Editors

Dr. Barys Shyrokau
E-Mail Website
Guest Editor
Department of Cognitive Robotics, Delft University of Technology, Mekelweg 2, NL - 2628 CD Delft, The Netherlands
Interests: vehicle dynamics and control; automated driving; model predictive control; optimal control
Special Issues and Collections in MDPI journals
Dr. Valentin Ivanov
E-Mail Website
Guest Editor
Automotive Engineering Group, Technische Universität Ilmenau, Ehrenbergstr. 15, 98693 Ilmenau, Germany
Interests: vehicle dynamics; electric vehicles; automotive control systems
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

For the coming decades, automated driving (AD) is probably the most promising but also the most challenging area of innovation in the automotive industry. The relevant Roadmaps and Action Plans worldwide predict the exploitation of high automation within the 2020s, stating that safety, comfort, and user acceptance are the topics with the most research focus. Increasing requirements lead to the development of complex vehicle subsystems to achieve better operation characteristics. Another challenge related to AD is the amount of testing required. Based on Toyota studies, approximately 14.2 billion kilometers of testing are needed to make conclusions about AD safety. Large amounts of testing with diverse participants will also be needed to test and ensure AD comfort and acceptance.

For this Special Issue of Vehicles entitled “Dynamics and Control of Automated Vehicles”, we are looking for original research within this domain. The topics of interest within the scope of this Special Section include (but are not limited to) the following:

  • Novel design of AD powertrain and chassis subsystems;
  • Predictive and learning based methods to improve AD safety and performance;
  • Estimation and sensing for AD vehicle;
  • User-automated vehicle interaction focusing on AD comfort and acceptance;
  • New testing and assessment methods for rapid AD evaluation;
  • Fail-safety aspects of AD design.

Dr. Valentin Ivanov
Dr. Barys Shyrokau
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Vehicles is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Automated driving
  • New vehicle concepts
  • Vehicle dynamics
  • Vehicle control
  • Driving comfort
  • Human–machine interaction
  • Driving simulator
  • Chassis engineering
  • Fail-safety
  • Testing

Published Papers (4 papers)

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Research

Open AccessArticle
Integrated Braking Control for Electric Vehicles with In-Wheel Propulsion and Fully Decoupled Brake-by-Wire System
Vehicles 2021, 3(2), 145-161; https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles3020009 - 25 Mar 2021
Viewed by 617
Abstract
This paper introduces a case study on the potential of new mechatronic chassis systems for battery electric vehicles, in this case a brake-by-wire (BBW) system and in-wheel propulsion on the rear axle combined with an integrated chassis control providing common safety features like [...] Read more.
This paper introduces a case study on the potential of new mechatronic chassis systems for battery electric vehicles, in this case a brake-by-wire (BBW) system and in-wheel propulsion on the rear axle combined with an integrated chassis control providing common safety features like anti-lock braking system (ABS), and enhanced functionalities, like torque blending. The presented controller was intended to also show the potential of continuous control strategies with regard to active safety, vehicle stability and driving comfort. Therefore, an integral sliding mode (ISM) and proportional integral (PI) control were used for wheel slip control (WSC) and benchmarked against each other and against classical used rule-based approach. The controller was realized in MatLab/Simulink and tested under real-time conditions in IPG CarMaker simulation environment for experimentally validated models of the target vehicle and its systems. The controller also contains robust observers for estimation of non-measurable vehicle states and parameters e.g., vehicle mass or road grade, which can have a significant influence on control performance and vehicle safety. Full article
(This article belongs to the Special Issue Dynamics and Control of Automated Vehicles)
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Open AccessArticle
Comparison of Typical Controllers for Direct Yaw Moment Control Applied on an Electric Race Car
Vehicles 2021, 3(1), 127-144; https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles3010008 - 27 Feb 2021
Viewed by 858
Abstract
Direct Yaw Moment Control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer and faster on a race track. [...] Read more.
Direct Yaw Moment Control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer and faster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, a more advanced comparison of the important characteristics of the controllers’ performance is lacking, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle, and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified Proportional Integral Derivative (PID) controller showed that its performance is comparable to other more complex control techniques such as Model Predictive Control (MPC). Full article
(This article belongs to the Special Issue Dynamics and Control of Automated Vehicles)
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Open AccessArticle
Musculoskeletal Driver Model for the Steering Feedback Controller
Vehicles 2021, 3(1), 111-126; https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles3010007 - 24 Feb 2021
Viewed by 736
Abstract
This paper aims to find a mathematical justification for the non-linear steady state steering haptic response as a function of driver arm posture. Experiments show that different arm postures, that is, same hands location on the steering wheel but at different initial steering [...] Read more.
This paper aims to find a mathematical justification for the non-linear steady state steering haptic response as a function of driver arm posture. Experiments show that different arm postures, that is, same hands location on the steering wheel but at different initial steering angles, result in a change in maximum driver arm stiffness. This implies the need for different steering torque response as a function of steering angle, which is under investigation. A quasi-static musculoskeletal driver model considering elbow and shoulder joints is developed for posture analysis. The torque acting in the shoulder joint is higher than in the elbow. The relationship between the joint torque and joint angle is linear in the shoulder, whereas the non-linearity occurs in the elbow joint. The simulation results qualitatively indicate a similar pattern as compared to the experimental muscle activity results. Due to increasing muscle non-linearity at high steering angles, the arm stiffness decreases and then the hypothesis suggests that the effective steering stiffness is intentionally reduced for a consistent on-center haptic response. Full article
(This article belongs to the Special Issue Dynamics and Control of Automated Vehicles)
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Open AccessArticle
MPC-Based Motion-Cueing Algorithm for a 6-DOF Driving Simulator with Actuator Constraints
Vehicles 2020, 2(4), 625-647; https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles2040036 - 02 Dec 2020
Viewed by 1987
Abstract
Driving simulators are widely used for understanding human–machine interaction, driver behavior and in driver training. The effectiveness of simulators in this process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion-cueing strategies have provided reasonable results, these [...] Read more.
Driving simulators are widely used for understanding human–machine interaction, driver behavior and in driver training. The effectiveness of simulators in this process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion-cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is nonlinear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and use maximum workspace. Furthermore, adaptive weights-based tuning is used to smooth the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace use. Full article
(This article belongs to the Special Issue Dynamics and Control of Automated Vehicles)
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